Automated systems and analysis procedures for text-based interactions (email, chat, and social media) rely on text models of language with domain-specific information. Configuration, training, and translation can be expensive and time-consuming processes that require experts in the language and the domain. It is often difficult to justify the large financial and time costs associated with employing several people to create translations in multiple languages. There is also a lack of consistency in translation methodology and cultural adaptation.
Automatic machine translation of language can be problematic as simple substitution of words in one language for words in another does not typically produce a good translation. Within limited domains, machine translation may be effective, but machine translation in an interactive environment is ineffective and leads to customer dissatisfaction.
The complexity and expense of domain-specific translation in an interactive environment encourages the development of a new approach to address these issues. Additionally, the new approach needs to be a living model, one that is not static and does not require expensive periodic intervention by translators to remain current.